A Shared WIL: Investigating University Approaches to Supporting Students in Securing Work-Integrated Learning Opportunities
Bibliographic record
Abstract
Work-integrated learning (WIL) is a pedagogical tool that integrates practical experiences within a student’s academic studies. However, a student’s uptake in WIL courses is dependent on their ability to secure a work experience, which can undermine the institution’s responsibility to establish adequate support systems that facilitate access to such opportunities. This study investigates how centralized WIL units in Ontario are providing and prioritizing resources to support student participation and success in securing WIL opportunities. Through the lens of activity theory, the findings of a multi-site case study suggest there are no significant gaps in the number of resources available to students, though various cultural-historical components influence the allocation and prioritization of resources during the securement phase of WIL, including an overlap of WIL and co-op policies, staffing limitations, and challenges managing faculty expectations. This study emphasizes institutional accountability and urges a deeper examination into how WIL practitioners prioritize student support.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".